AI FOR VISUAL BRAND MANAGEMENT IN PRINT MEDIA

Authors

  • Dr. Ganesh Waghmare MIT College of Management, MIT Art, Design and Technology University, Pune, India
  • Rajesh Raikwar Assistant Professor, Department of Electrical Engineering, Vishwakarma Institute of Technology, Pune, Maharashtra, 411037, India
  • Gurpreet Kaur Associate Professor, School of Business Management, Noida International University, Greater Noida 203201, India
  • Shanthi P Assistant Professor, Meenakshi College of Arts and Science, Meenakshi Academy of Higher Education and Research, Chennai, Tamil Nadu 600101, India
  • Janmejay Shukla Ramdeobaba University, Nagpur, Maharashtra, India
  • Chaitali Department of Computer Science and Engineering, Shri Shankaracharya Institute of Professional Management and Technology, Raipur, Chhattisgarh, India

DOI:

https://doi.org/10.29121/shodhkosh.v7.i1s.2026.7117

Keywords:

AI-Driven Branding, Visual Brand Consistency, Print Media Analytics, Generative Design Systems, Brand Asset Management

Abstract [English]

Management of visual brands in print media is an important aspect of preserving brand identity, recognition, and consistency of large amount of marketing collateral. Nonetheless, the conventional brand governance is highly manualized, working on fixed rules, and judgmental, which is hard to scale, audit, and conform to quickly changing design ecosystems. The paper suggests an AI-based visual brand management system in the print media that uses machine learning, computer vision, and generative modeling to automate the brand review, consistency evaluation, and layout standardization. The suggested methodology is a mixture of image classification and clustering tools that are used to identify brand assets, i.e., logos, color codices, typography, and repetitive motifs in a variety of print materials. The new AI-based brand consistency scoring model is proposed to objectively assess how well its brand guidelines are followed by quantifying the degree of visual similarity, stylistic deviation and alignment of motifs on a component and layout level. Moreover, generative AI models are used to aid the idea of template creation and layout optimization to allow a standardized but flexible design output that can maintain brand identity and save time. The proposed experimental framework compares the proposed framework with the traditional rule-based and designer-driven review processes in terms of accuracy, consistency deviation, processing time, and scalability. Findings indicate that AI-driven solution can greatly increase the rate of brand consistency detection, lessen the time to do the review process, and increase consistency in print campaigns. This piece of work displays the potential of AI to act as a decision-support tool to a designer/brand manager instead of taking away human creativity by connecting analytics with creativity. The suggested framework provides a platform of scalable intelligent brand governance and preconditions the future expansions to include real-time, cross-platform, and privacy-aware brand management systems.

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Published

2026-02-17

How to Cite

Waghmare, G., Raikwar, R., Kaur, G., Shanthi P, Shukla, J., & Chaitali. (2026). AI FOR VISUAL BRAND MANAGEMENT IN PRINT MEDIA. ShodhKosh: Journal of Visual and Performing Arts, 7(1s), 421–430. https://doi.org/10.29121/shodhkosh.v7.i1s.2026.7117